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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: tasksource/deberta-small-long-nli
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- accuracy
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- precision
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- recall
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model-index:
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- name: toxicity-scorer
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# toxicity-scorer
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This model is a fine-tuned version of [tasksource/deberta-small-long-nli](https://huggingface.co/tasksource/deberta-small-long-nli) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1972
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- F1: 0.9191
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- Accuracy: 0.9205
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- Precision: 0.9181
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- Recall: 0.9205
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 128
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- total_eval_batch_size: 128
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|:---------:|:------:|
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| No log | 0 | 0 | 0.7648 | 0.5092 | 0.4397 | 0.8431 | 0.4397 |
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| 0.2012 | 1.0 | 8816 | 0.1993 | 0.9180 | 0.9200 | 0.9167 | 0.9200 |
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| 0.1929 | 2.0 | 17632 | 0.1973 | 0.9192 | 0.9204 | 0.9182 | 0.9204 |
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| 0.1991 | 3.0 | 26448 | 0.1972 | 0.9191 | 0.9205 | 0.9181 | 0.9205 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.5.1
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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